Analysis Of Correlation Algorithms For Shack-Hartmann Wavefront Sensors

Shack-Hartmann wavefront sensors calculate the position of focal spot in each sub-aperture from intensity distributions, the noises of the detector itself would have a certain impact on the detecting accuracy and would lead to inaccurate wavefront detections using conventional centroiding method. It has been demonstrated that the correlation algorithms with template matching is able to improve the accuracy. In this paper, several correlation algorithms such as absolute difference function, absolute difference function-squared, square difference function, cross-correlation function and normalized cross-correlation are compared at different signal-to-noise ratios. To further improve the accuracy, interpolation algorithms including equiangular line fitting, parabola interpolation, gauss interpolation and least square method are brought in, which turns out that least square method could minimize the detecting error. Besides, simulations within single aperture and full aperture both illustrate that cross-correlation function is most robust but needs more calculations, so is least square method. Moreover, although absolute difference function would be inaccurate at low signal-to-noise ratios, it still can obtain high detecting accuracy at high signal-to-noise ratios and it minimizes the calculations.